# Twitter User Media Scraper (`powerai/twitter-user-media-scraper`) Actor
Fetch media content (photos and videos) from any Twitter user's timeline, with auto-pagination and detailed metadata. Supports up to your specified maxResults.
- **URL**: https://apify.com/powerai/twitter-user-media-scraper.md
- **Developed by:** [PowerAI](https://apify.com/powerai) (community)
- **Categories:** Social media, Videos
- **Stats:** 80 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet
## Pricing
from $4.99 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## Twitter User Media Scraper
This actor allows you to fetch the media content (photos and videos) posted by a specified Twitter account. It uses the latest Twitter API interface and supports automatic pagination to collect up to the number of media items you specify.
### Features
- Fetches media content (photos and videos) from any Twitter user's timeline.
- Supports automatic pagination to retrieve large lists.
- Allows you to specify the maximum number of results (`maxResults`).
- Returns detailed information for each media item, including URLs and metadata.
### Input
- **screenname** (string, required): The Twitter username whose media you want to fetch.
- **maxResults** (integer, optional): Maximum number of media items to fetch. Default is 10.
### Output
The output is an array of media objects, each containing:
- `tweet_id`
- `bookmarks`
- `created_at`
- `favorites`
- `text`
- `lang`
- `source`
- `views`
- `quotes`
- `replies`
- `retweets`
- `conversation_id`
- `media` (containing photo and video information)
- `author` (user information)
### Example Input
```json
{
"screenname": "x",
"maxResults": 10
}
````
### Example Output
```json
[
{
"tweet_id": "1922699805056229677",
"bookmarks": 69,
"created_at": "Wed May 14 17:05:30 +0000 2025",
"favorites": 1637,
"text": "call me if you need your old @ back 🖤 https://t.co/pfLDzFaMrY",
"lang": "en",
"source": "Twitter Web App",
"views": "624940",
"quotes": 16,
"replies": 379,
"retweets": 181,
"conversation_id": "1922699805056229677",
"media": {
"photo": [
{
"media_url_https": "https://pbs.twimg.com/media/Gq7L8flW4AAvVmC.jpg",
"id": "1922698331064557568"
}
]
},
"author": {
"rest_id": "783214",
"name": "X",
"screen_name": "X",
"avatar": null,
"blue_verified": true
},
"quoted": {
"tweet_id": "1922661168729997670",
"bookmarks": 337,
"created_at": "Wed May 14 14:31:58 +0000 2025",
"favorites": 9228,
"text": "Your move, @X.",
"lang": "en",
"views": "1047484",
"quotes": 138,
"replies": 189,
"retweets": 1165,
"conversation_id": "1922661168729997670",
"author": {
"rest_id": "89090040",
"name": "Max",
"screen_name": "StreamOnMax",
"avatar": null,
"blue_verified": true
},
"media": []
},
"scrapedAt": "2025-05-30T01:20:24.243Z"
},
...
]
```
### Notes
- The actor will stop fetching once it reaches the specified `maxResults` or there are no more media items to fetch.
- Make sure the target account is public and not protected.
# Actor input Schema
## `screenname` (type: `string`):
The Twitter username whose media you want to fetch.
## `maxResults` (type: `integer`):
Maximum number of media items to fetch.
## Actor input object example
```json
{
"screenname": "x",
"maxResults": 10
}
```
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"screenname": "x",
"maxResults": 10
};
// Run the Actor and wait for it to finish
const run = await client.actor("powerai/twitter-user-media-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"screenname": "x",
"maxResults": 10,
}
# Run the Actor and wait for it to finish
run = client.actor("powerai/twitter-user-media-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"screenname": "x",
"maxResults": 10
}' |
apify call powerai/twitter-user-media-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=powerai/twitter-user-media-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Twitter User Media Scraper",
"description": "Fetch media content (photos and videos) from any Twitter user's timeline, with auto-pagination and detailed metadata. Supports up to your specified maxResults.",
"version": "0.0",
"x-build-id": "fWoN2CLEgwpihFy2k"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/powerai~twitter-user-media-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-powerai-twitter-user-media-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/powerai~twitter-user-media-scraper/runs": {
"post": {
"operationId": "runs-sync-powerai-twitter-user-media-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/powerai~twitter-user-media-scraper/run-sync": {
"post": {
"operationId": "run-sync-powerai-twitter-user-media-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"screenname"
],
"properties": {
"screenname": {
"title": "Twitter Username",
"type": "string",
"description": "The Twitter username whose media you want to fetch.",
"default": "x"
},
"maxResults": {
"title": "Max Results",
"minimum": 10,
"maximum": 10000,
"type": "integer",
"description": "Maximum number of media items to fetch.",
"default": 10
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```